Agentweaver MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Agentweaver MCP Serverstart a new agent run to add error handling to the payment module"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Agentweaver
⚠️ Alpha software. Agentweaver is under active development. Expect breaking changes and incomplete features. Do not use it in production.
Run teams of AI agents on your own infrastructure.
Describe the work you want done. Agentweaver can generate the agent roles, skills, and workflow for that work, then run the team in isolated environments on infrastructure you control.
Workflows turn probabilistic agent work into a governed path toward a defined outcome, with the gates and approvals you set. Start and supervise work in the Agentweaver interface or through MCP from an assistant, editor, or CLI.

📖 Read the documentation or browse the source in docs/index.md.
Why Agentweaver
Generate the team and process. Start from a description or reusable blueprint to define roles, skills, and the workflow the agents follow.
Set review gates. Confirm the intended outcome before work starts and approve the assembled result before it merges.
Inspect every run. Watch agent events and topology live. Runs keep their work in isolated git worktrees.
Use your preferred surface. Operate the same projects, teams, workflows, and runs from the web interface or an MCP client.
Carry context forward. Team memory and decisions give later runs prior constraints and learnings.
Related MCP server: harness_to_mcp
What it includes
Capability | What it does |
Binds a repository and AI configuration to teams, runs, and memory. | |
Defines reusable roles, policies, and agent teams. | |
Runs configurable multi-role flows for delivery, research, content, operations, and evaluation. | |
Organizes work and shows active orchestration from plan to review. | |
Uses an RAI check and human approval before a result merges. | |
Lets MCP clients work with Agentweaver through authenticated tools. |
Quick start
Install Git, Node.js, and the .NET 10 SDK. On Windows, install WSL2 and bubblewrap before you run local agent work.
git clone https://github.com/sabbour/agentweaver.git
cd agentweaver
npm run setup
npm run devnpm run setup prepares the local application. npm run dev starts the API at http://localhost:5000 and the web UI at http://localhost:5173.
Before you sign in, configure local authentication and model access. The Getting started guide has platform setup, authentication, and first-run instructions.
Learn more
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Maintenance
Related MCP Connectors
Give any MCP-compatible AI assistant a builder for live, hosted web tools and workflows.
Your org's AI agents, tasks, runs, search, and brain files as MCP tools and resources.
One MCP endpoint for Claude, GPT & Gemini: 100+ tools + no-code connectors + agent workers.
- QuallaaOAuthcom.quallaa
Talk to your public-facing AI from any MCP client — Claude, ChatGPT, Cursor, Cline, Windsurf.
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